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You're reading from  Practical Machine Learning Cookbook

Product typeBook
Published inApr 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781785280511
Edition1st Edition
Languages
Python
Tools
Apache Spark
Concepts
Machine Learning
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Author (1)
Atul Tripathi
Atul Tripathi
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Atul Tripathi

Atul Tripathi has spent more than 11 years in the fields of machine learning and quantitative finance. He has a total of 14 years of experience in software development and research. He has worked on advanced machine learning techniques, such as neural networks and Markov models. While working on these techniques, he has solved problems related to image processing, telecommunications, human speech recognition, and natural language processing. He has also developed tools for text mining using neural networks. In the field of quantitative finance, he has developed models for Value at Risk, Extreme Value Theorem, Option Pricing, and Energy Derivatives using Monte Carlo simulation techniques.
Read more about Atul Tripathi

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Self-organizing map - visualizing of heatmaps

Over the past decade, there has been exponential growth in information. Gaining new knowledge from such databases is difficult, costly, and time-consuming if done manually. It may even be impossible when the data exceeds certain limits of size and complexity. As a result, the automated analysis and visualization of massive multidimensional datasets have been the focus of much scientific research over the last few years. The principal objective of this analysis and visualization is to find regularities and relationships in the data, thereby gaining access to hidden and potentially useful knowledge. A self-organizing map (SOM) is an unsupervised neural network algorithm that projects high-dimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map.

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Practical Machine Learning Cookbook
Published in: Apr 2017Publisher: PacktISBN-13: 9781785280511
© 2017 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Atul Tripathi

Atul Tripathi has spent more than 11 years in the fields of machine learning and quantitative finance. He has a total of 14 years of experience in software development and research. He has worked on advanced machine learning techniques, such as neural networks and Markov models. While working on these techniques, he has solved problems related to image processing, telecommunications, human speech recognition, and natural language processing. He has also developed tools for text mining using neural networks. In the field of quantitative finance, he has developed models for Value at Risk, Extreme Value Theorem, Option Pricing, and Energy Derivatives using Monte Carlo simulation techniques.
Read more about Atul Tripathi

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